code: def _get_torch_exploration_action(self, action_dist, explore):
      if explore:
          return action_dist.inputs.argmax(dim=-1), None
      else:
          scores = self.model.value_function()
          return scores.argmax(dim=-1), None
  
file_path: ray/python/ray/rllib/utils/exploration/upper_confidence_bound.py
imports: from typing import Union
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.utils.annotations import override, PublicAPI
  from ray.rllib.utils.exploration.exploration import Exploration
  from ray.rllib.utils.framework import TensorType, try_import_tf
label_desc: Use image node_id 2 for calling the UpperConfidenceBound obj's underlying member method code with example usage: obj._get_torch_exploration_action(action_dist, explore) and returns: action_dist,  None, scores,  None